As mobile Internet and mobile smart devices and terminals develop constantly, wireless hotspots become one of the requisite facilities and services for individuals, homes and enterprises, and in service industries such as, restaurants, hotels and retail. A wireless hotspot may generally cover a distance of about 50 meters indoor. If a user scans or connects with the wireless hotspot, it may be believed that the user accesses a Point of Interest (POI) where the wireless hotspot locates. Hence, the POI accessed by the user offline may be inferred based on the wireless hotspot information scanned or connected by the user and a matching relationship between the wireless hotspot and the POI.
In solutions in the existing art, there are mainly three approaches of calculating and collecting the matching relationship between the wireless hotspot and the POI:
1) Collecting by a dedicated employee hired by a company or enterprise. The company or enterprise may specifically assign a dedicated employee and provide equipment and training to collect the matching information between the wireless hotspot and the POI.
2) Collecting using user uploaded data, i.e., encouraging the user to sign at the POI where the user locates while connecting the wireless hotspot, and thereby obtaining the matching relationship between the wireless hotspot and the POI.
3) Matching surrounding POI names based on SSID of the wireless hotspot.
However, the above approaches have their own drawbacks:
1) Regarding the approach of collecting by a dedicated employee specifically assigned by a company or enterprise, the main disadvantage of the approach is in low efficiency and high costs. On the one hand, the number of employed collecting employees is limited, an information collection speed and efficiency are not high, and a relatively long time is needed to complete the collection covering main cities and business areas. On the other hand, assigning dedicated employees, providing equipment and performing outdoor collection result in relatively high costs and large outlay.2) Regarding the approach of collecting using user uploaded data, based on the crowdsourcing idea, the efficiency of collecting data in this approach is higher than the approach of directly assigning dedicated employees for collection, but the data-collecting accuracy is relatively difficult to control.3) Regarding the approach of matching with surrounding POI names based on the SSID of the wireless hotspot, the approach exhibits a higher matching accuracy but a lower coverage because not all POIs provided with SSID of the wireless hotspot are directly related to the POI names.